Based on our record, Uppy should be more popular than Neuro. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Look at https://uppy.io/ open source and lot of integrations. You can keep moving to different levels of abstraction as required and see some good practices of how things are done. - Source: Hacker News / about 2 months ago
I just found uppy. This will be the next one I use. https://uppy.io/. Source: 12 months ago
I’m building a photo sharing website and want to make it incredibly easy to upload photos. Of course I could just utilize AWS official packages but that’s pretty bare bones. I could also use next-s3-upload which is purpose built for Next and simplifies some things but is still fairly basic. But then there’s things like uppy that provides everything you’d ever need in an uploaded (third party sources, camera, etc.)... Source: about 1 year ago
Media file uploads with the Uppy JavaScript uploader plugin. Source: over 1 year ago
I would look at Uppy.js, I've used it in an enterprise application and it works super well, makes it super easy to do what you're trying to achieve with progress bars for each file. Source: over 1 year ago
Projects are definitely the best way to learn models. Build things for fun that do things in topics/fields that you care about or think is cool. a few years ago when I was getting into ML stuff I build fantasy football things that weren't even useful but provided an actual use case. Then I did more complicated stuff with photography and lighting because I did real estate photography. As far as ML libraries go,... Source: almost 3 years ago
So far I’ve seen AWS Sagemaker kind of allows for a situation like this, but would rather not deal with all that config. Algorithmia and Nuclio are too enterprise focused. Neuro is new and looks great, but from my understanding I would still need to create a lambda instance myself that then calls neuro’s servers - too indirect. Is there a total solution out there for this? Source: almost 3 years ago
A couple of weeks ago I put out a post on DeepSpeech running on the serverless setup at Neuro (https://getneuro.ai), and I've now got Silero running there as well. I've found this model is a lot faster than DS and way more accurate. Seeing around 300ms per request at the moment, hopefully will be closer to 100ms soon but this is a pretty decent speed in this application already. Source: about 3 years ago
I just made a streaming script connecting Deepspeech to serverless GPUs at Neuro (https://getneuro.ai). Was a fun piece of work, and cool to play around with. You can find the source here: https://github.com/neuro-ai-dev/npu_examples/tree/main/deepspeech. Source: over 3 years ago
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